Bits & Bytes

ONNXRuntime for ML inference now in preview. Microsoft released a preview of the ONNX Runtime, a high-performance inference engine for Open Neural Network Exchange (ONNX) models. It is compatible with ONNX version 1.2 and comes in Python packages that support both CPU and GPU.

Uber describes new platform for rapid Python ML development. Uber shared Michelangelo PyML, an extension to its Michelangelo platform providing for faster development and experimentation based on Docker containers.

NYU and Facebook release cross-language NLU data set. As researchers look to increase the number of languages NLU systems can understand, gathering and annotating data in every language is a bottleneck. One alternative is to train a model on data in one language and then test that model in other languages. The Cross-Lingual Natural Language Inference (XNLI) data set advances this approach by providing that test data in languages.

Malongresearchers develop a technique to train deep neural networks. In this new paper, Malong introduces CurriculumNet, a training strategy leveraging curriculum learning to increase performance while decreasing noise when working on large sets of data. The code is now available on GitHub as well.